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README.md
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---
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language:
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- mn
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: distilbert-base-multilingual-cased-ner-demo
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# distilbert-base-multilingual-cased-ner-demo
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1687
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- Precision: 0.8684
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- Recall: 0.8891
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- F1: 0.8786
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- Accuracy: 0.9693
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.2009 | 1.0 | 572 | 0.1271 | 0.8074 | 0.8440 | 0.8253 | 0.9590 |
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| 0.0951 | 2.0 | 1144 | 0.1069 | 0.8469 | 0.8768 | 0.8616 | 0.9671 |
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| 0.063 | 3.0 | 1716 | 0.1136 | 0.8486 | 0.8783 | 0.8632 | 0.9680 |
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| 0.0444 | 4.0 | 2288 | 0.1221 | 0.8506 | 0.8808 | 0.8654 | 0.9675 |
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| 0.0303 | 5.0 | 2860 | 0.1389 | 0.8576 | 0.8823 | 0.8698 | 0.9677 |
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| 0.0217 | 6.0 | 3432 | 0.1457 | 0.8683 | 0.8878 | 0.8779 | 0.9685 |
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| 0.0157 | 7.0 | 4004 | 0.1542 | 0.8661 | 0.8873 | 0.8766 | 0.9692 |
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| 0.0121 | 8.0 | 4576 | 0.1615 | 0.8730 | 0.8878 | 0.8803 | 0.9694 |
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| 0.0094 | 9.0 | 5148 | 0.1675 | 0.8683 | 0.8883 | 0.8782 | 0.9688 |
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| 0.0077 | 10.0 | 5720 | 0.1687 | 0.8684 | 0.8891 | 0.8786 | 0.9693 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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